Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

Abstract

Molecular similarity is a key concept in drug discovery. It is based on the assumption that structurally similar molecules frequently have similar properties. Assessment of similarity between small molecules has been highly effective in the discovery and development of various drugs. Especially, two-dimensional (2D) similarity approaches have been quite popular due to their simplicity, accuracy and efficiency. Recently, the focus has been shifted toward the development of methods involving the representation and comparison of three-dimensional (3D) conformation of small molecules. Among the 3D similarity methods, evaluation of shape similarity is now gaining attention for its application not only in virtual screening but also in molecular target prediction, drug repurposing and scaffold hopping. A wide range of methods have been developed to describe molecular shape and to determine the shape similarity between small molecules. The most widely used methods include atom distance-based methods, surface-based approaches such as spherical harmonics and 3D Zernike descriptors, atom-centered Gaussian overlay based representations. Several of these methods demonstrated excellent virtual screening performance not only retrospectively but also prospectively. In addition to methods assessing the similarity between small molecules, shape similarity approaches have been developed to compare shapes of protein structures and binding pockets. Additionally, shape comparisons between atomic models and 3D density maps allowed the fitting of atomic models into cryo-electron microscopy maps. This review aims to summarize the methodological advances in shape similarity assessment highlighting advantages, disadvantages and their application in drug discovery.

Optimizing Electrostatic Similarity for Virtual Screening: A New Methodology

“…This database is useful since in the high similarity cases it would directly contribute to drug re-purposing. This is of relevant utility given the clear trend regarding re-purposing drugs observed over the last 5 years (Dakshanamurthy et al, 2012;Kumar and Zhang, 2018;Yuan et al, 2017).…”

Molecular docking and network connections of active compounds from the classical herbal formula Ding Chuan Tang

“…Single pharmaceutical compounds, such as the majority of asthma medications, fundamentally target single molecular mechanisms and as a result may be less efficient at treating complex diseases that have multi-cellular/tissue pathology (Kumar & Zhang, 2018;Aggarwal et al, 2007). It has been proposed that pharmaceuticals targeting molecular signaling pathways are the future for drug discovery as they target multiple protein targets and pathways (Kumar & Zhang, 2018;Aggarwal et al, 2007).…”

“…Single pharmaceutical compounds, such as the majority of asthma medications, fundamentally target single molecular mechanisms and as a result may be less efficient at treating complex diseases that have multi-cellular/tissue pathology (Kumar & Zhang, 2018;Aggarwal et al, 2007). It has been proposed that pharmaceuticals targeting molecular signaling pathways are the future for drug discovery as they target multiple protein targets and pathways (Kumar & Zhang, 2018;Aggarwal et al, 2007). The network connection results of this investigation are in line with this theory, as the pharmacological and mechanistic predictions provide evidence, albeit computational, of 155 strong affinity binding connections (≥−9.0 kcal/mol) between DCT-compounds and five proteins associated with multiple asthma KEGG disease pathways (Fig.…”

Maximum common property: a new approach for molecular similarity

“…Many methods to describe the shape of molecules have been developed. Surface-based approaches such as 3D Zernike descriptors and others demonstrated a good virtual screening performance [25]. Futhermore, nowadays there is a wide variety of web services, source code libraries and frameworks such as Open Babel [26], CoSiAn [27], ChemMapper [28], SMSD Toolkit [29], Corina [30], ISIDA-Platform [31], Chemaxon Web Services [32], and Chemical Development Kit (CDK) library [33] that allow to calculate 2D and 3D descriptors, build and validate QSAR models, and support the implementation of new computational models and algorithms.…”